• Posted
    Monday, February 3, 2020 - 10:30

Maximizing uptime with intelligent vibration monitoring and predictive analytics

Application Study - Understanding critical component performance
Using real-time monitoring to understand in-service machine vibration keeps machines running; allowing predictive instead of reactive maintenance, as well as historical trend analysis and comparisons between machines and operating environments.

Real-time alerts and historical analysis - Using SensorCloud with the MathEngine analytics tool provides characterization metrics between machines and operating environments, through the equipment life-cycle.

Machine health monitoring - Measuring in-use vibration of factory equipment allows predictive maintenance in high-value production processes.

Cloud computing and big data tools have greatly reduced the costs associated with processing large volumes of sensor data common to many industrial vibration applications. SensorCloud’s industrial customers are leveraging these new capabilities to deploy condition based monitoring and prognostics systems at a fraction of the cost and installation time of traditional systems.